Cloud computing allows dynamic resource scaling for enterprise online transaction systems, one of the
key characteristics that differentiates the cloud from the traditional computing paradigm. However,
initializing a new virtual instance in a cloud is not instantaneous; cloud hosting platforms introduce
several minutes delay in the hardware resource allocation. In this paper, we develop prediction-based
resource measurement and provisioning strategies using Neural Network and Linear Regression to satisfy
upcoming resource demands.
Experimental results demonstrate that the proposed technique offers more adaptive resource
management for applications hosted in the cloud environment, an important mechanism to achieve ondemand
resource allocation in the cloud.